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2023 19th international conference on Wireless and Mobile computing, Networking and Communications, WiMob 2023

2023 19th International Conference on Wireless and Mobile Co...

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19th ieee international conference on Wireless and Mobile computing, Networking and Communications, WiMob 2023

ISBN: (纸本)9798350336672

the proceedings contain 81 papers. the topics discussed include: outage performance of IRS-assisted underwater optical wireless communication systems over combined channel model;sensor-based wastewater monitoring framework to detect COVID-19;deep learning assisted channel estimation for cell-free distributed MIMO networks;multi-agent Q-learning for drone base stations;RF fingerprint-based identity verification in the presence of an sei mimicking adversary;analyzing the feasibility of privacy-respecting automated tracking of devices fleeing a burglary;security implications of a satellite communication device on wireless networks using Pentesting;deep learning assisted quality ranking for list decoding of videos subject to transmission errors;robotaxis as computing clusters: a stochastic modeling approach;chained estimation for data reduction-driven routing in wireless sensor networks;lightweight group pre-handover authentication scheme for aviation 5g air-to-ground networks;learning to detect wireless spectrum occupancy using clustering approaches;smartphone camera as a diagnostic tool for detection of pulse rate and blood oxygen concentration;density-aware reinforcement learning to optimize energy efficiency in UAV-assisted networks;area under time series transformation for home appliance classification;and a novel single grant-based uplink scheme for high throughput and reliable low latency communication.

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Communication-Efficient -Stepping for distributed computing systems 19

Communication-Efficient -Stepping for Distributed Computing ...

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19th ieee international conference on Wireless and Mobile computing, Networking and Communications, WiMob 2023

作者： Zhang, Haomeng Xie, Junfei Zhang, Xinyu Department of Electrical and Computer Engineering United States San DiegoCA92182 United States SDSU Department of Electrical and Computer Engineering San DiegoCA92182 United States UCSD Department of Electrical and Computer Engineering La Jolla CA92093 United States

ISBN: (纸本)9798350336672

this paper considers the single source shortest path (SSSP) problem, which is the key for many applications such as navigation, mapping, routing, and social networking. Existing SSSP algorithms are designed mostly for shared-memory systems. Nevertheless, with the prevalence of diverse smart devices like drones, there is a growing interest in deploying SSSP algorithms over distributed computing systems so that they can run efficiently onboard of smart devices via Mobile Ad Hoc computing or at the network edges via Mobile Edge computing. In this paper, we introduce a communication-efficient -stepping algorithm for distributed computing systems. the proposed algorithm is featured by 1) a message coordination architecture for reducing message exchanges between workers, 2) a pruning technique for reducing redundant computations, and 3) an aggregation technique for further reducing message exchanges when communication delay is significant. theoretical analyses and experimental studies on real-world graph datasets demonstrate the promising performance of proposed algorithm. © 2023 ieee.

关键词： Human resource management

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NETREACT: distributed Event Detection in sensor Data Streams with Disaggregated Packet Processing Pipelines 8

NETREACT: Distributed Event Detection in Sensor Data Streams...

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8th ieee international conference on Network Softwarization (NetSoft) - Network Softwarization Coming of Age - New Challenges and Opportunities

作者： Gyorgyi, Csaba Kecskemeti, Karoly Mallouhi, Hiba Voros, Peter Laki, Sandor Eotvos Lorand Univ Budapest Hungary

ISBN: (纸本)9781665406949

A new phenomenon called in-network computing has recently emerged with the aim of offloading calculations beyond the traditional task of packet forwarding to network switches. One of the most studied in-network computing applications is processing of sensor data streams. Existing works such as FastReact focus on solving this problem using flexible SmartNICs. In this paper, we propose NETREACT: an improved ASIC-oriented design for distributed event detection in sensor data streams to achieve a disaggregated processing pipeline. In contrast to existing approaches, NETREACT distributes the event detection task among a set of switches while leveraging the capabilities of the Intel Tofino platform in terms of boosting throughput and reducing latency. the proposed event-rule disaggregation method has the advantage of overcoming the hardware resource constraints and improving the overall network performance.

关键词： P4 in-network computing pipeline disaggregation event detection sensor data processing

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Deep Neural Network Algorithm to Improve Link Reliability in Wireless sensor Networks 4

Deep Neural Network Algorithm to Improve Link Reliability in...

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4th international conference on Electronics and Sustainable Communication systems, ICESC 2023

作者： Vijaya Bhaskar, K. Kumanan, T. Sree Southry, S. Elangovan, Vetrimani Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Dr Mgr Educational and Research Institute Department of Computer Science and Engineering Tamil Nadu Chennai India Sona College of Technology Department of Electronics and Communication Engineering Tamil Nadu Salem India Presidency University Department of Computer Science and Engineering Karnataka Bangalore India

ISBN: (纸本)9798350300093

Wireless sensor Network (WSN) is distinguished by size, dynamism, and decentralization. these complicated properties give rise to various problems, one of which is the impact of wireless communications on the efficiency of networks and the protocols used for routing. the prediction methods of link reliability can boost the efficiency of the routing algorithms used in WSNs while preventing weak connections. this approach introduces a Deep neural network algorithm to improve link reliability (DILR) in WSN. A Deep neural network (DNN) algorithm is used to evaluate the input parameters like node Received Signal Strength, available bandwidth, delay, and packet received rate parameters for calculating the link reliability output. the available bandwidth parameter recognizes the efficient data transmitting path. the experimental outcomes illustrate that the DILR mechanism improves the link reliability among nodes and reduces routing overhead compared to the conventional mechanism. © 2023 ieee.

关键词： Deep neural networks

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Quantum Computer Metrics and HPC Center Environmental sensor Data Analysis Towards Fidelity Prediction 4

Quantum Computer Metrics and HPC Center Environmental Sensor...

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4th ieee international conference on Quantum computing and Engineering, QCE 2023

作者： Ahmed, Hossam Deng, Xiaolong Heller, Helmut Guillen, Carla Zulfiqar, Asim Ruefnacht, Martin Jamadagni, Amit Tovey, Matthew Schulz, Martin Schulz, Laura Leibniz Supercomputing Centre Garching Germany Technical University of Munich Garching Germany

ISBN: (纸本)9798350343236

A tight integration of quantum accelerators with high-performance computers (HPC) necessitates relocating the often highly sensitive quantum devices from controlled laboratory environments to noisy data centers. Various factors impacting fidelity must be tracked and mitigated to ensure the performance of quantum computers in such environments. this paper describes a monitoring system utilizing Internet of things (IoT) technology incorporating multiple sensors to gather and feed data into a data center-wide database. the data collected is then analyzed to identify correlations between fidelity and environmental factors. Using this data, we propose a novel, adaptive calibration mechanism in which a machine learning model predicts the optimal calibration timing for the quantum computer based on fidelity prediction with varying environmental conditions. In the larger scope, this research aims to enhance our understanding of fidelity-altering factors and develop strategies for maintaining optimal quantum computer performance in real-world, noisy data center environments. © 2023 ieee.

关键词： Data Analytics

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Design of MEMS based Electric sensor for Tomographic Applications 4

Design of MEMS based Electric Sensor for Tomographic Applica...

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4th international conference on Electronics and Sustainable Communication systems, ICESC 2023

作者： Shameem, Syed. Tummala, Rasathvika Dkhaalid, S.M. Varma, K Gowtham Bharath Rohitha, D. Divvyasree, L. Kl University Koneru Lakshmaiah Education Foundation Department of Ece Vaddeswaram India

ISBN: (纸本)9798350300093

the main motivation for this work is that most Indians who are involved in accidents or have other injuries will ignore minor cracks. Some days later, there will be severe effects from these, like swelling, damaged tissues, etc. this will become a serious issue in day-to-day life. the two main reasons for the negligence are inadequate availability of scanning equipment and people cannot afford to pay high prices for scanning. As a result, there is a need of designing a low-cost hand-held scanner such that the scanners will be available in each and every clinic or small hospital. So that the injured persons can consult their nearest doctor and can have a scanning test right away. there are many types of scanning techniques available on the market, such as x-ray, CT scan, MRI, and so on, but the cost of these is very high. Also, there are some adverse effects to using these scanners. X-rays send the rays into the body so that there may be a chance of damaging the tissues. To overcome these problems, this study has proposed MEMS based electric sensor for Tomography methodology. the technique is based on Electronic Impedance, which has very negligible damage to the tissues and can also be used as a user-friendly scanner. © 2023 ieee.

关键词： Computerized tomography

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Towards Ambiently Powered Inference on Wireless sensor Networks: Asynchrony is the Key! 17

Towards Ambiently Powered Inference on Wireless Sensor Netwo...

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17th Annual ieee international conference on distributed computing in sensor systems (ieee DCOSS)

作者： Papageorgiou, Vasileios Nichoritis, Athanasios Vasilakopoulos, Panagiotis Vougioukas, Georgios Bletsas, Aggelos Tech Univ Crete Sch Elect & Comp Engn Khania 73100 Greece

ISBN: (纸本)9781665439299

Is it possible to build ultra-low power wireless sensor networks (WSN) that exploit the inherent parallel and distributed nature of powerful message passing/inference algorithms, embrace ultra-low power communication principles and make autonomous, in-network decisions, solely powered by the environment? While edge and cloud computing emerge, this work points towards the opposite direction, inspired by the fact that ambient energy, either from radio frequency (RF), sun, motion, temperature or even living organisms, has fixed (on average) density per surface (or volume). It is shown, perhaps for the first time in the literature (to the best of our knowledge), a proof of concept, where a WSN harvests energy from the environment and processes itself the collected information in a distributed manner, by converting the (network) inference task to a probabilistic, message passing problem. Examples from Gaussian Belief Propagation and Average Consensus are offered;ambient energy harvesting and availability are quantified, controling the probability of successful (or not) message passing. Such interrupted communication requires distributed algorithms robust to asynchrony, at the expense of increased overall delay. Simulation and experimental validation are offered in a WSN testbed with solar energy harvesting. Future work will focus on overall delay minimization.

关键词： Wireless communication Wireless sensor networks Message passing Solar energy sensor systems Delays Low-power electronics

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Position sensor Fault Prognostic using Data Driven Approach 4

Position Sensor Fault Prognostic using Data Driven Approach

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4th international conference for Emerging Technology, INCET 2023

作者： Pawar, Mahesh Y Sewalkar, Swarupanand Guerra, Ageda John Deere India Pvt. Ltd. Enterprise Technology & Engineering Center Pune India John Deere Enterprise Technology & Engineering Center Monterrey Mexico

ISBN: (纸本)9798350335750

Resolver is a widely used in the feedback loop of the PM traction drive to find exact rotary position of the permanent magnet. In real systems, position error is caused by various factors such as amplitude imbalance, imperfect quadrature, inductive harmonics, reference phase shift, excitation signal distortion or other disturbance signals. this has influence on motor torque production. So, it is crucial to monitor resolver performance so that failed sensor can be easily replaced. this also benefits supply chain to keep the parts *** paper demonstrates monitoring the health of the resolver sensor using a data driven approach. the algorithm developed is not only capable of classifying faulty/ healthy resolver, but it can also show the amount of degradation in the resolver sensor. the state-of-the-art developed neural network model is trained on the robust database covering all possible resolver degradations, partial and complete failures. this model is developed on a complete synthetic data tapped from the Simulink model and it is further optimized for the accuracy and size. the algorithm was initially tested on the standalone open-loop resolver model which later extended for the closed-loop version. It also supports commanded mode of prognostics which can detect and classify possible harness faults of the resolver sensor. the proposed algorithm has shown high confidence when it is tested offline on the actual hardware data. © 2023 ieee.

关键词： Permanent magnets

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Proceedings of 2022 ieee 4th international conference on Civil Aviation Safety and Information Technology, ICCASIT 2022

Proceedings of 2022 IEEE 4th International Conference on Civ...

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4th ieee international conference on Civil Aviation Safety and Information Technology, ICCASIT 2022

ISBN: (纸本)9781665467667

the proceedings contain 276 papers. the topics discussed include: research on image classification improvement based on convolutional neural networks with mixed training;a single-reader indoor localization method based on multi-objective evolutionary algorithm optimization of deep model;a framework for multi-variate time series anomaly detection based on behavioral patterns in electric vehicles;service restoration algorithm of distribution power system;a prediction method of 5G base station cell traffic based on improved transformer model;research on trusted sharing and privacy computing technology of energy data in supply chain based on alliance chain;sub-tree division based routing and spectrum assignment for multicast in fixed/flex-grid optical networks;and scheduler architecture and key features in distributed computing.

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Few-Shot Φ-OTDR Event Identification Based on Attention Prototypical Network 4

Few-Shot Φ-OTDR Event Identification Based on Attention Pro...

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4th international Computational Imaging conference, CITA 2024

作者： Hu, Liqin Li, Yujiao Qin, Ying Yu, Kuanglu Visual Intellgence +X International Cooperation Joint Laboratory of MOE Beijing100044 China Institute of Information Science School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China

ISBN: (纸本)9781510688834

Phase-sensitive optical time-domain reflectometer (Φ-OTDR) is a distributed, highly sensitive optical sensing system with high localization accuracy, and it is widely used in the fields of intrusion identification, pipeline monitoring, and et al. With the rapid development of machine learning and deep learning, it has become a major trend to utilize these advanced methods for Φ-OTDR disturbance event identification. Although these methods can achieve better results when trained on large-scale datasets, in practice, the low appearing frequency of certain category of events and the difficulty in data collection lead to a lack of training samples. In addition, labeling the collected samples is a time-consuming and labor-intensive task. In order to solve all the above problems and improve the classification performance of Φ-OTDR disturbance events with limited samples, we propose a method based on an attention prototypical network. Under the setting of 3-way 3-shot, i.e. only 3 samples per category, our method achieves a remarkable accuracy of 93.02%, demonstrating high validity and reliability in the few-shot disturbance event classification task. the experimental results show that our method has the potential to be applied in distributed fiber optic sensor systems, providing reliable technical support for practical engineering applications. © 2025 SPIE.

关键词： Reflectometers

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